Requirements

Have hands-on experience building and operating large-scale observability or monitoring infrastructure
Have deep, hands-on experience with observability signals end to end—from instrumentation through ingest to query and analysis
Understand high-throughput telemetry pipelines and the tradeoffs involved in collecting, storing, and querying operational data at scale
Are comfortable digging below the application layer into the kernel, the network stack, or the hardware
Have excellent communication skills and enjoy partnering with internal teams to improve their operational visibility and incident response capabilities
Are excited about building foundational infrastructure and comfortable navigating ambiguous, high-impact technical challenges, both independently and with a team

Nice to Haves

10+ years of relevant industry experience, including building and operating large-scale observability or monitoring infrastructure
Experience building or operating eBPF-based observability in production—tracing, profiling, or network visibility
Experience running continuous profiling at fleet scale, including managing overhead budgets and symbolization
Kernel- and syscall-level debugging experience and performance engineering craft
Experience profiling or instrumenting accelerator workloads
Experience operating metrics systems at very high cardinality, or large-scale telemetry storage backends
Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies
Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting

Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure
Build observability solutions that give engineers deep, low-overhead visibility into system behavior across the fleet
Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth
Build instrumentation libraries, SDKs, and eBPF-based auto-instrumentation to emit high-quality telemetry, with and without code changes
Reduce mean time to detection and resolution by building cross-signal correlation—from kernel-level events up to application traces—unified query interfaces, and AI-assisted diagnostic tooling
Drive fleet-wide efficiency by turning continuous profiling and utilization telemetry into actionable optimization insights across CPU, memory, and accelerator fleets
Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organization